Effects of anthropogenic noise on fishes at the SGaan Kinghlas-Bowie Seamount Marine Protected Area
Bibliographic record
Abstract
Underwater noise from anthropogenic sources has been increasing dramatically for the past few decades and little is known about its effects on fishes. The objective of this study is to describe the occurrence and characteristics of fish sounds in the SGaan Kinghlas-Bowie Seamount Marine Protected Area (SK-B MPA, British Columbia, Canada) and to correlate them with the corresponding anthropogenic soundscape. Here we present preliminary results of the detection of fish sounds at SK-B MPA between July 2011 and July 2013. An automatic detector was used on nearly 40,000 acoustic samples (4,754.5 hours in total) to search for fish sounds. About 1.2% of the data were highlighted as containing fish-like signals. Manual verification of these detections revealed that 95.5% were false positives and the remaining sounds were of unknown origin. Eighty detections were highly stereotyped and are suspected to be produced by fish, but no identification has been confirmed yet. Systematic manual inspection of sub-sampled acoustic data is yet to be performed to determine if the detector missed any fish sounds. Future deployments should select areas based on the presence of known fish habitat occurrence, and install autonomous recorders optimized to reduce equipment self-noise and flow noise biases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".